Impact of Users' Cultural Background on Multi-faceted Trust-based Recommender Systems
Contributo in Atti di convegno
Data di Pubblicazione:
2023
Abstract:
Trust-based recommender systems usually overlook the cultural background of people when making suggestions. In this paper, we propose some strategies to include the home country of users in trust-based recommendation algorithms and we aim to understand if this information can improve the recommender system performance.
Tipologia CRIS:
04A-Conference paper in volume
Keywords:
Cultural Background of Users; Multi-faceted Reputation Model; Recommender systems; Social Relations; Trust-based Recommender Systems; Web searching and information discovery
Elenco autori:
Mauro Noemi; Hu Zhongli Filippo; Petrone Giovanna; Segnan Marino; Mattutino Claudio
Link alla scheda completa:
Link al Full Text:
Titolo del libro:
Joint Workshops of IUI 2023: HAI-GEN - Human-AI Co-Creation with Generative Models, ITAH - Workshop on Interactive Technologies for AI in Healthcare, MILC - Workshop on Intelligent Music Interfaces for Listening and Creation, SHAI - Workshop on Designing for Safety in Human-AI Interactions, SketchRec - Workshop on Sketch Recognition and SOCIALIZE - Social and Cultural Integration with Personalized Interfaces
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